Neuroimaging alterations and relapse in early-stage psychosis.

BACKGROUND: Recent reports have indicated that symptom exacerbation after a period of improvement, referred to as relapse, in early-stage psychosis could result in brain changes and poor disease outcomes. We hypothesized that substantial neuroimaging alterations may exist among patients who experience relapse in early-stage psychosis. METHODS: We studied patients with psychosis within 2 years after the first psychotic event and healthy controls. We divided patients into 2 groups, namely those who did not experience relapse between disease onset and the magnetic resonance imaging (MRI) scan (no-relapse group) and those who did experience relapse between these 2 timings (relapse group). We analyzed 3003 functional connectivity estimates between 78 regions of interest (ROIs) derived from resting-state functional MRI data by adjusting for demographic and clinical confounding factors. RESULTS: We studied 85 patients, incuding 54 in the relapse group and 31 in the no-relapse group, along with 94 healthy controls. We observed significant differences in 47 functional connectivity estimates between the relapse and control groups after multiple comparison corrections, whereas no differences were found between the no-relapse and control groups. Most of these pathological signatures (64%) involved the thalamus. The Jonckheere-Terpstra test indicated that all 47 functional connectivity changes had a significant cross-group progression from controls to patients in the no-relapse group to patients in the relapse group. LIMITATIONS: Longitudinal studies are needed to further validate the involvement and pathological importance of the thalamus in relapse. CONCLUSION: We observed pathological differences in neuronal connectivity associated with relapse in early-stage psychosis, which are more specifically associated with the thalamus. Our study implies the importance of considering neurobiological mechanisms associated with relapse in the trajectory of psychotic disorders.

Mary has a little chair: Eliciting noun-modifier phrases in individuals with acute post-stroke aphasia.

Background: Aphasia assessment primarily examines an individual's syntax, nouns, and verbs. However, modifiers, such as adjectives and number words, and bound morphemes can be the subject of considerable difficulty for individuals with aphasia. The Morphosyntactic Generation (MorGen) targets nouns, modifiers, and bound inflectional morphemes in two-word phrases among people with aphasia. Aims: The purpose of this work is to provide the first report of the MorGen in hyperacute-acute aphasia. In doing so, we aim to (1) examine the MorGen's concurrent validity with common assessments of aphasia; (2) describe performance in modifiers by people with acute aphasia; and (3) associate MorGen performance with extent of lesioned vascular territories in acute stroke. Methods & Procedures: 62 adult English speakers within the first 14 days of left hemisphere ischemic stroke and 61 healthy control participants completed the MorGen. In addition to receiving the MorGen, participants with stroke received the Western Aphasia Battery (WAB), Boston Naming Test, and Hopkins Action Naming Assessment. Clinical MRIs were analyzed for the extent of lesion in the vascular territory of the left anterior, medial, and posterior cerebral artery, as well as the left posterior choroidal and thalamoperforator arteries. Outcomes & Results: Aim 1: Performance on the MorGen demonstrated consistently high, significant correlations with that on the WAB, Boston Naming Test, and Hopkins Action Naming Assessment. Aim 2: Individuals who had a stroke but were within functional limits (WFL) on the WAB performed significantly worse than healthy controls on the MorGen, driven by differences in adjective performance. When controlling for aphasia severity, those with fluent aphasia performed significantly better in their production of nouns, plurals, number, size, and color than those who had non-fluent aphasia, but both groups were similarly inclined to omit genitive marking. Aim 3: Lesions in the territory of the temporal branch of the posterior cerebral artery were associated with poorer performance in nouns, size, and color. Lesions in the territory of the anterior cerebral artery were associated with poorer performance in numbers. Conclusions: This work highlights the value of the MorGen as a tool for post-stroke language evaluation that complements the skills captured in more widely-used assessments such as the WAB and BNT.

A whole-brain neuromark resting-state fMRI analysis of first-episode and early psychosis: Evidence of aberrant cortical-subcortical-cerebellar functional circuitry.

Psychosis (including symptoms of delusions, hallucinations, and disorganized conduct/speech) is a main feature of schizophrenia and is frequently present in other major psychiatric illnesses. Studies in individuals with first-episode (FEP) and early psychosis (EP) have the potential to interpret aberrant connectivity associated with psychosis during a period with minimal influence from medication and other confounds. The current study uses a data-driven whole-brain approach to examine patterns of aberrant functional network connectivity (FNC) in a multi-site dataset comprising resting-state functional magnetic resonance images (rs-fMRI) from 117 individuals with FEP or EP and 130 individuals without a psychiatric disorder, as controls. Accounting for age, sex, race, head motion, and multiple imaging sites, differences in FNC were identified between psychosis and control participants in cortical (namely the inferior frontal gyrus, superior medial frontal gyrus, postcentral gyrus, supplementary motor area, posterior cingulate cortex, and superior and middle temporal gyri), subcortical (the caudate, thalamus, subthalamus, and hippocampus), and cerebellar regions. The prominent pattern of reduced cerebellar connectivity in psychosis is especially noteworthy, as most studies focus on cortical and subcortical regions, neglecting the cerebellum. The dysconnectivity reported here may indicate disruptions in cortical-subcortical-cerebellar circuitry involved in rudimentary cognitive functions which may serve as reliable correlates of psychosis.

Longitudinal imaging highlights preferential basal ganglia circuit atrophy in Huntington's disease.

Huntington's disease is caused by a CAG repeat expansion in the Huntingtin gene (HTT), coding for polyglutamine in the Huntingtin protein, with longer CAG repeats causing earlier age of onset. The variable 'Age' × ('CAG'-L), where 'Age' is the current age of the individual, 'CAG' is the repeat length and L is a constant (reflecting an approximation of the threshold), termed the 'CAG Age Product' (CAP) enables the consideration of many individuals with different CAG repeat expansions at the same time for analysis of any variable and graphing using the CAG Age Product score as the X axis. Structural MRI studies have showed that progressive striatal atrophy begins many years prior to the onset of diagnosable motor Huntington's disease, confirmed by longitudinal multicentre studies on three continents, including PREDICT-HD, TRACK-HD and IMAGE-HD. However, previous studies have not clarified the relationship between striatal atrophy, atrophy of other basal ganglia structures, and atrophy of other brain regions. The present study has analysed all three longitudinal datasets together using a single image segmentation algorithm and combining data from a large number of subjects across a range of CAG Age Product score. In addition, we have used a strategy of normalizing regional atrophy to atrophy of the whole brain, in order to determine which regions may undergo preferential degeneration. This made possible the detailed characterization of regional brain atrophy in relation to CAG Age Product score. There is dramatic selective atrophy of regions involved in the basal ganglia circuit-caudate, putamen, nucleus accumbens, globus pallidus and substantia nigra. Most other regions of the brain appear to have slower but steady degeneration. These results support (but certainly do not prove) the hypothesis of circuit-based spread of pathology in Huntington's disease, possibly due to spread of mutant Htt protein, though other connection-based mechanisms are possible. Therapeutic targets related to prion-like spread of pathology or other mechanisms may be suggested. In addition, they have implications for current neurosurgical therapeutic approaches, since delivery of therapeutic agents solely to the caudate and putamen may miss other structures affected early, such as nucleus accumbens and output nuclei of the striatum, the substantia nigra and the globus pallidus.

Mixed longitudinal and cross-sectional analyses of deep gray matter and white matter using diffusion weighted images in premanifest and manifest Huntington's disease.

Changes in the brain of patients with Huntington's disease (HD) begin years before clinical onset, so it remains critical to identify biomarkers to track these early changes. Metrics derived from tensor modeling of diffusion-weighted MRIs (DTI), that indicate the microscopic brain structure, can add important information to regional volumetric measurements. This study uses two large-scale longitudinal, multicenter datasets, PREDICT-HD and IMAGE-HD, to trace changes in DTI of HD participants with a broad range of CAP scores (a product of CAG repeat expansion and age), including those with pre-manifest disease (i.e., prior to clinical onset). Utilizing a fully automated data-driven approach to study the whole brain divided in regions of interest, we traced changes in DTI metrics (diffusivity and fractional anisotropy) versus CAP scores, using sigmoidal and linear regression models. We identified points of inflection in the sigmoidal regression using change-point analysis. The deep gray matter showed more evident and earlier changes in DTI metrics over CAP scores, compared to the deep white matter. In the deep white matter, these changes were more evident and occurred earlier in superior and posterior areas, compared to anterior and inferior areas. The curves of mean diffusivity vs. age of HD participants within a fixed CAP score were different from those of controls, indicating that the disease has an additional effect to age on the microscopic brain structure. These results show the regional and temporal vulnerability of the white matter and deep gray matter in HD, with potential implications for experimental therapeutics.

A large public dataset of annotated clinical MRIs and metadata of patients with acute stroke.

To extract meaningful and reproducible models of brain function from stroke images, for both clinical and research proposes, is a daunting task severely hindered by the great variability of lesion frequency and patterns. Large datasets are therefore imperative, as well as fully automated image post-processing tools to analyze them. The development of such tools, particularly with artificial intelligence, is highly dependent on the availability of large datasets to model training and testing. We present a public dataset of 2,888 multimodal clinical MRIs of patients with acute and early subacute stroke, with manual lesion segmentation, and metadata. The dataset provides high quality, large scale, human-supervised knowledge to feed artificial intelligence models and enable further development of tools to automate several tasks that currently rely on human labor, such as lesion segmentation, labeling, calculation of disease-relevant scores, and lesion-based studies relating function to frequency lesion maps.

Automatic comprehensive radiological reports for clinical acute stroke MRIs.

BACKGROUND: Although artificial intelligence systems that diagnosis among different conditions from medical images are long term aims, specific goals for automation of human-labor, time-consuming tasks are not only feasible but equally important. Acute conditions that require quantitative metrics, such as acute ischemic strokes, can greatly benefit by the consistency, objectiveness, and accessibility of automated radiological reports. METHODS: We used 1,878 annotated brain MRIs to generate a fully automated system that outputs radiological reports in addition to the infarct volume, 3D digital infarct mask, and the feature vector of anatomical regions affected by the acute infarct. This system is associated to a deep-learning algorithm for segmentation of the ischemic core and to parcellation schemes defining arterial territories and classically-identified anatomical brain structures. RESULTS: Here we show that the performance of our system to generate radiological reports was comparable to that of an expert evaluator. The weight of the components of the feature vectors that supported the prediction of the reports, as well as the prediction probabilities are outputted, making the pre-trained models behind our system interpretable. The system is publicly available, runs in real time, in local computers, with minimal computational requirements, and it is readily useful for non-expert users. It supports large-scale processing of new and legacy data, enabling clinical and translational research. CONCLUSION: The generation of reports indicates that our fully automated system is able to extract quantitative, objective, structured, and personalized information from stroke MRIs.

Artificial intelligence (AI) uses computer software to solve problems that normally require human input. It is likely that AI will take over, or help with, certain tasks in medical imaging, particularly where these tasks are time-consuming and laborious for clinicians. Here, we demonstrate the possibility of using AI to generate radiological reports for brain scans from patients who have had a stroke. These reports provide a summary of what is shown in the scans, and are normally written by clinicians. Our system performs similarly to human experts, is fast, publicly available, and runs on normal computers with minimal computational requirements, meaning that it might be a useful tool for researchers and clinicians to use when assessing and treating patients with stroke.

Subacute aphasia recovery is associated with resting-state connectivity within and beyond the language network.

OBJECTIVE: To examine changes to connectivity after aphasia treatment in the first 3 months after stroke. METHODS: Twenty people experiencing aphasia within the first 3 months of stroke completed MRI before and immediately following 15 hours of language treatment. They were classified based on their response to treatment on a naming test of nouns as either high responders (10% improvement or more), or low responders (<10% improvement). Groups were similar in age, gender distribution, education, days since stroke, stroke volume, and baseline severity. Resting-state functional connectivity analysis was limited to the connectivity of the left fusiform gyrus with the bilateral inferior frontal gyrus, supramarginal gyrus, angular gyrus, and superior, middle, and inferior temporal gyrus, based on previous studies showing the importance of left fusiform gyrus in naming performance. RESULTS: Baseline ipsilateral connectivity between the left fusiform gyrus and the language network was similar between high and low responders to therapy when controlling for stroke volume. Following therapy, change in connectivity was significantly greater among high responders between the left fusiform gyrus and the ipsilateral and contralateral pars triangularis, ipsilateral pars opercularis and superior temporal gyrus, and contralateral angular gyrus when compared with low responders. INTERPRETATION: An account of these findings incorporates primarily proximal connectivity restoration, but also potentially reflects select contralateral compensatory reorganization. The latter is often associated with chronic recovery, reflecting the transitional nature of the subacute period.

Relation between white matter integrity, perfusion, and processing speed in early-stage schizophrenia.

OBJECTIVE: Cerebral blood flow (CBF) plays a critical role in the maintenance of neuronal integrity, and CBF alterations have been linked to deleterious white matter changes. Several studies report CBF and white matter structural alterations individually. However, whether and how these pathological changes relate to each other remains elusive. By using our cohort of individuals with early-stage schizophrenia, we investigated the relationship between CBF and white matter structure. METHOD: We studied 51 early-stage schizophrenia patients and age- and sex-matched healthy controls. We investigated the relationship among tissue structure (assessed with diffusion weighted imaging), perfusion (accessed by pseudo-continuous arterial labeling imaging), and neuropsychological indices (focusing on processing speed). We focused on the corpus callosum, due to its major role in associative functions and directness on revealing the architecture of a major white matter bundle. We performed mediation analysis to identify the possible mechanism underlay the relationship among cognition and white matter integrity and perfusion. RESULTS: The CBF and the fractional anisotropy (FA) were inversely correlated in the corpus callosum of early-stage schizophrenia patients. While CBF negatively correlated with processing speed, FA correlated positively with this cognitive measure. These results were not observed in controls. Mediation analysis revealed that the effect of FA on processing speed was mediated via the CBF. CONCLUSIONS: We provide evidence of a relationship between brain perfusion and white matter integrity in the corpus callosum in early-stage schizophrenia. These findings may shed the light on underlying metabolic support for structural changes with cognitive impact in schizophrenia.

Association of inferior division MCA stroke location with populations with atrial fibrillation incidence.

BACKGROUND AND AIM: Considering the anatomical features of Middle Cerebral Artery (MCA) bifurcation, larger emboli are more likely to enter the inferior division over the superior division. Since emboli of cardiac origin are larger on average than emboli of arterial origin, we hypothesize that the infarcts in temporal and parietal lobes are more likely associated to atrial fibrillation than those in the frontal lobes, therefore occurring more often in populations with higher incidence of atrial fibrillation, such as male (compared to women) and white (compared to black) patients. METHODS: We included 197 patients with MCA "temporoparietal predominant" infarcts and 105 with "frontal predominant" infarcts. Variations between stroke location (frontal or temporoparietal), sex, and race were examined via Chi-square test. RESULTS: Male patients were more likely than female patients to be afflicted by temporoparietal strokes versus frontal strokes, while white patients had greater likelihood than black patients to be afflicted by temporoparietal strokes versus frontal strokes. Patients with confirmed diagnosis of atrial fibrillation display more temporoparietal strokes compared to frontal strokes. CONCLUSION: Temporoparietal MCA ischemic strokes occur more frequently in male and white patients: populations with known increased incidence of atrial fibrillation. In addition, population-specific anatomical characteristics of the MCA bifurcation might favor the larger cardiac emboli to enter the inferior division and cause temporoparietal infarcts. This association can help guide search for the most likely etiology of infarcts.

Automatic comprehensive aspects reports in clinical acute stroke MRIs.

The Alberta Stroke Program Early CT Score (ASPECTS) is a simple visual system to assess the extent and location of ischemic stroke core. The capability of ASPECTS for selecting patients' treatment, however, is affected by the variability in human evaluation. In this study, we developed a fully automatic system to calculate ASPECTS comparable with consensus expert readings. Our system was trained in 400 clinical diffusion weighted images of patients with acute infarcts and evaluated with an external testing set of 100 cases. The models are interpretable, and the results are comprehensive, evidencing the features that lead to the classification. This system adds to our automated pipeline for acute stroke detection, segmentation, and quantification in MRIs (ADS), which outputs digital infarct masks and the proportion of diverse brain regions injured, in addition to the predicted ASPECTS, the prediction probability and the explanatory features. ADS is public, free, accessible to non-experts, has very few computational requirements, and run in real time in local CPUs with a single command line, fulfilling the conditions to perform large-scale, reproducible clinical and translational research.

Digital 3D Brain MRI Arterial Territories Atlas.

The locus and extent of brain damage in the event of vascular insult can be quantitatively established quickly and easily with vascular atlases. Although highly anticipated by clinicians and clinical researchers, no digital MRI arterial atlas is readily available for automated data analyses. We created a digital arterial territory atlas based on lesion distributions in 1,298 patients with acute stroke. The lesions were manually traced in the diffusion-weighted MRIs, binary stroke masks were mapped to a common space, probability maps of lesions were generated and the boundaries for each arterial territory was defined based on the ratio between probabilistic maps. The atlas contains the definition of four major supra- and infra-tentorial arterial territories: Anterior, Middle, Posterior Cerebral Arteries and Vertebro-Basilar, and sub-territories (thalamoperforating, lenticulostriate, basilar and cerebellar arterial territories), in two hierarchical levels. This study provides the first publicly-available, digital, 3D deformable atlas of arterial brain territories, which may serve as a valuable resource for large-scale, reproducible processing and analysis of brain MRIs of patients with stroke and other conditions.

Identifying brain hierarchical structures associated with Alzheimer's disease using a regularized regression method with tree predictors.

Brain segmentation at different levels is generally represented as hierarchical trees. Brain regional atrophy at specific levels was found to be marginally associated with Alzheimer's disease outcomes. In this study, we propose an ℓ1 -type regularization for predictors that follow a hierarchical tree structure. Considering a tree as a directed acyclic graph, we interpret the model parameters from a path analysis perspective. Under this concept, the proposed penalty regulates the total effect of each predictor on the outcome. With regularity conditions, it is shown that under the proposed regularization, the estimator of the model coefficient is consistent in ℓ2 -norm and the model selection is also consistent. When applied to a brain sMRI dataset acquired from the Alzheimer's Disease Neuroimaging Initiative (ADNI), the proposed approach identifies brain regions where atrophy in these regions demonstrates the declination in memory. With regularization on the total effects, the findings suggest that the impact of atrophy on memory deficits is localized from small brain regions, but at various levels of brain segmentation. Data used in preparation of this paper were obtained from the ADNI database.

Emotional and qualitative outcomes among patients with left and right hemisphere stroke.

The differences in mental health outcomes of right and left hemisphere strokes are well studied; however, there is a long-standing controversy surrounding whether depression is associated with lateralization of stroke or not. In this investigation, we examined the effect of lesion location on post-stroke depression controlling for lesion size and hemiparesis in a longitudinal sample assessed at acute, subacute, and chronic timepoints. As a secondary aim, we further examined the effect of lesion location on self-reported difficulties across a wide array of domains. A series of 134 patients with left hemisphere strokes and 79 with right hemisphere strokes completed the Patient Health Questionnaire-9 and an inventory of post-stroke abilities at within acute, subacute, and chronic windows following stroke. When controlling for hemiparesis and overall lesion volume, we found no difference in depression between groups at any timepoint. Additional exploratory analyses provided a further look at differing challenges associated with depression in each group.

Regularized regression on compositional trees with application to MRI analysis.

A compositional tree refers to a tree structure on a set of random variables where each random variable is a node and composition occurs at each non-leaf node of the tree. As a generalization of compositional data, compositional trees handle more complex relationships among random variables and appear in many disciplines, such as brain imaging, genomics and finance. We consider the problem of sparse regression on data that are associated with a compositional tree and propose a transformation-free tree-based regularized regression method for component selection. The regularization penalty is designed based on the tree structure and encourages a sparse tree representation. We prove that our proposed estimator for regression coefficients is both consistent and model selection consistent. In the simulation study, our method shows higher accuracy than competing methods under different scenarios. By analyzing a brain imaging data set from studies of Alzheimer's disease, our method identifies meaningful associations between memory decline and volume of brain regions that are consistent with current understanding.

Left Hemisphere Bias of NIH Stroke Scale Is Most Severe for Middle Cerebral Artery Strokes.

NIHSS score is higher for left vs. right hemisphere strokes of equal volumes. However, differences in each vascular territory have not been evaluated yet. We hypothesized that left vs. right differences are driven by the middle cerebral artery (MCA) territory, and there is no difference between hemispheres for other vascular territories. This study is based on data from 802 patients with evidence of acute ischemic stroke in one major arterial territory (MCA, n = 437; PCA, n = 209; ACA, n = 21; vertebrobasilar, n = 46). We examined differences in patients with left or right strokes regarding to lesion volume, NIHSS, and other covariates (age, sex, race). We used linear models to test the effects of these covariates on NIHSS. We looked at the whole sample as well as in the sample stratified by NIHSS (≤5 or >5) and by lesion location (MCA or PCA). Patients with left MCA strokes had significantly higher NIHSS than those with right strokes. Only patients with MCA strokes showed NIHSS score affected by the hemisphere when controlling for stroke volume and patient's age. This difference was driven by the more severe strokes (NIHSS>5). It is important to consider this systematic bias in the NIHSS when using the score for inclusion criteria for treatment or trials. Patients with right MCA stroke may be under-treated and left with disabling deficits that are not captured by the NIHSS.

Structural and Functional Brain Connectivity Uniquely Contribute to Episodic Memory Performance in Older Adults.

In this study, we examined the independent contributions of structural and functional connectivity markers to individual differences in episodic memory performance in 107 cognitively normal older adults from the BIOCARD study. Structural connectivity, defined by the diffusion tensor imaging (DTI) measure of radial diffusivity (RD), was obtained from two medial temporal lobe white matter tracts: the fornix and hippocampal cingulum, while functional connectivity markers were derived from network-based resting state functional magnetic resonance imaging (rsfMRI) of five large-scale brain networks: the control, default, limbic, dorsal attention, and salience/ventral attention networks. Hierarchical and stepwise linear regression methods were utilized to directly compare the relative contributions of the connectivity modalities to individual variability in a composite delayed episodic memory score, while also accounting for age, sex, cerebrospinal fluid (CSF) biomarkers of amyloid and tau pathology (i.e., Aß42/Aß40 and p-tau181), and gray matter volumes of the entorhinal cortex and hippocampus. Results revealed that fornix RD, hippocampal cingulum RD, and salience network functional connectivity were each significant independent predictors of memory performance, while CSF markers and gray matter volumes were not. Moreover, in the stepwise model, the addition of sex, fornix RD, hippocampal cingulum RD, and salience network functional connectivity each significantly improved the overall predictive value of the model. These findings demonstrate that both DTI and rsfMRI connectivity measures uniquely contributed to the model and that the combination of structural and functional connectivity markers best accounted for individual variability in episodic memory function in cognitively normal older adults.

Neural regions underlying object and action naming: Complementary evidence from acute stroke and primary progressive aphasia.

Background: Naming impairment is commonly noted in individuals with aphasia. However, object naming receives more attention than action naming. Furthermore, most studies include participants with aphasia due to only one aetiology, commonly stroke. We developed a new assessment, the Hopkins Action Naming Assessment (HANA), to evaluate action naming impairments. Aims: Our aims were to show that the HANA is a useful tool that can (1) identify action naming impairments and (2) be used to investigate the neural substrates underlying naming. We paired the HANA with the Boston Naming Test (BNT) to compare action and object naming. We considered participants with aphasia due to primary progressive aphasia (PPA) or acute left hemisphere stroke to provide a more comprehensive picture of brain-behaviour relationships critical for naming. Behaviourally, we hypothesised that there would be a double dissociation between object and action naming performance. Neuroanatomically, we hypothesised that different neural substrates would be implicated in object vs. action naming and that different lesion-deficit associations would be identified in participants with PPA vs. acute stroke. Methods & Procedures: Participants (N=138 with PPA, N=37 with acute stroke) completed the BNT and HANA. Behavioural performance was compared. A subset of participants (N=31 with PPA, N=37 with acute stroke) provided neuroimaging data. The whole brain was automatically segmented into regions of interest (ROIs). For participants with PPA, the image variables were the ROI volumes, normalised by the brain volume. For participants with acute stroke, the image variables were the percentage of each ROI affected by the lesion. The relationship between ROIs likely to be involved in naming performance was modelled with LASSO regression. Outcomes & Results: Behavioural results showed a double dissociation in performance: in each group, some participants displayed intact performance relative to healthy controls on actions but not objects and/or significantly better performance on actions than objects, while others showed the opposite pattern. These results support the need to assess both objects and actions when evaluating naming deficits. Neuroimaging results identified different regions associated with object vs. action naming, implicating overlapping but distinct networks of regions. Furthermore, results differed for participants with PPA vs. acute stroke, indicating that critical information may be missed when only one aetiology is considered. Conclusions: Overall, the study provides a more comprehensive picture of the neural bases of naming, underscoring the importance of assessing both objects and actions and considering different aetiologies of damage. It demonstrates the utility of the HANA.

Application of the dual stream model to neurodegenerative disease: Evidence from a multivariate classification tool in primary progressive aphasia.

Background: A clinical diagnosis of primary progressive aphasia relies on behavioral characteristics and patterns of atrophy to determine a variant: logopenic; nonfluent/agrammatic; or semantic. The dual stream model (Hickok & Poeppel, 2000; 2004; 2007; 2015) is a contemporary paradigm that has been applied widely to understand brain-behavior relationships; however, applications to neurodegenerative diseases like primary progressive aphasia are limited. Aims: The primary aim of this study is to determine if the dual stream model can be applied to a neurodegenerative disease, such as primary progressive aphasia, using both behavioral and neuroimaging data. Methods & Procedures: We analyzed behavioral and neuroimaging data to apply a multivariate classification tool (support vector machines) to determine if the dual stream model extends to primary progressive aphasia. Sixty-four individuals with primary progressive aphasia were enrolled (26 logopenic variant, 20 nonfluent/agrammatic variant, and 18 semantic variant) and administered four behavioral tasks to assess three linguistic domains (naming, repetition, and semantic knowledge). We used regions of interest from the dual stream model and calculated the cortical volume for gray matter regions and white matter structural volumes and fractional anisotropy. We applied a multivariate classification tool (support vector machines) to distinguish variants based on behavioral performance and patterns of atrophy. Outcomes & Results: Behavioral performance discriminates logopenic from semantic variant and nonfluent/agrammatic from semantic variant. Cortical volume distinguishes all three variants. White matter structural volumes and fractional anisotropy primarily distinguish nonfluent/agrammatic from semantic variant. Regions of interest that contribute to each classification in cortical and white matter analyses demonstrate alignment of logopenic and nonfluent/agrammatic variants to the dorsal stream, while the semantic variant aligns with the ventral stream. Conclusions: A novel implementation of an automated multivariate classification suggests that the dual stream model can be extended to primary progressive aphasia. Variants are distinguished by behavioral and neuroanatomical patterns and align to the dorsal and ventral streams of the dual stream model.